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SUPPLY CHAIN AND OPERATIONS CLUB

AAROHAN '18

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THE ONES THAT COUNT

Achieving Business Objectives By Driving Operational Excellence

In The Age Of Disruption

Lean and Six Sigma Excellence Awards

Co-Sponsor:

FASHION & RETAIL

Knowledge Partner:

SYMBIOSIS CENTRE FOR MANAGEMENT AND HUMAN RESOURCE DEVELOPMENT

LEAN AND SIX SIGMA EXCELLENCE AWARDS

AAROHAN 2018

AAROHAN 2018


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THE EVENT

The ‘Lean and Six Sigma Excellence Awards’ is an effort

from SCMHRD to recognize and honor those Corporates

who strive to set new benchmarks in the sphere of quality

and efficiency.

The selection parameters are first decided upon by a team of

eminent panelists, followed by the official invitations to the

Corporates for participation. The projects received are then

evaluated by the panelists on the previously decided

parameters.

The best projects under each category are chosen and their

team members are then invited to make their presentations at

the regional rounds held at Bengaluru, Delhi and Pune. The

best projects under each category from the regional rounds

are then shortlisted and invited to make the presentations at

the final round at SCMHRD, Pune, where they go through a

final round of scrutiny. At the concluding day of the event,

the winners are felicitated.

In our fourteenth year of hosting this event, we are proud to

say, that the ‘Lean and Six Sigma Excellence Awards’ has

accomplished new heights and has gained recognition among

the Corporate to an extent where they have started

considering these awards as a milestone in their six-sigma

journey. We promise to work at making the LSSEA the most

prestigious award in the field in the years to come.

FACULTY MEMBERS

Manoj Hudnurkar

Abhijit Bhagwat

Suhas Ambekar

TEAM MEMBERS

Senior Team

Aditi Luthra

Akash Bidkar

Anirudh Chauhan

Jatin Rathod

Kanika Tewatia

Mahima Ken

Navdeep Saini

Nakul Mundra

Reshma Sam

Sumati Gidronia

Varun Malik

Junior Team

Aditi Rana

Akshaya Verma

C Siddarth

Ishita Prakash

Keval Shah

Mandar Balshankar

Nishad Baxi

Nishanth Modupalli

Rebecca Fernandes

Sofiya

Vaibhav Makkar

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From the Desk of the Chancellor,

Symbiosis International (Deemed University)

Dear All, It gives me immense pleasure in welcoming you to the ‘Lean and Six Sigma Excellence

Awards, 2018’. Given today’s economic scenario, when organizations across all sectors are making an effort

to minimize the effects of the slowdown on their day to day operations, it is Six Sigma concepts

that hold special importance for one and all. Consistency in quality while minimizing waste is

what will help us all in this trying period. Six Sigma is not only about correcting errors but also about continuously innovating what seems

perfect and this is what we strive to do at Symbiosis. At Symbiosis, we aim to improve the efficiency and effectiveness of all those who are

a part of the Symbiosis fraternity. Hence Six Sigma is somewhere at the root of all that

we do. Wishing you all the very best for all your future endeavors. Best Wishes,

Dr. S.B. Mujumdar

Chancellor,


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From the Desk of the Pro Chancellor,


Dear All,

I am pleased to welcome you all to the ‘Lean and Six Sigma Excellence Awards, 2018’.

SCMHRD has always worked on improving the quality of its curriculum year after year to benefit its students. This event is the manifestation of the same drive.

I am happy to see the respect, this institute, as well as this current event has

drawn from the Corporate. My best wishes for all your future endeavors.

Best Wishes,

Dr. Vidya Yeravdekar

Pro Chancellor, Symbiosis International (Deemed University) & Principal Director,

Symbiosis

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From the Desk of the Vice Chancellor,


Dear All,

I am delighted to welcome you to ‘The Lean and Six Sigma Excellence Awards 2018’

that is hosted by SCMHRD every year.

I appreciate the efforts taken by SCMHRD, to not only felicitate Corporate who have

taken Six Sigma initiatives and reaped benefits from them, but also to build a platform

where everyone who is interested in Quality can learn a lot from the experiences of

others.

We at Symbiosis believe in harnessing and disseminating knowledge to the youth

today for better quality tomorrow.

All the very best to all of you!

Best Wishes, Dr. Rajani R Gupte

Vice Chancellor,


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From the Desk of the Director,

Symbiosis Centre for Management and Human

Resource Development

Welcome to SCMHRD ‘Lean and Six Sigma Excellence Awards, 2018’.

In today’s crisis struck world, very few think in terms of growth. One needs to

consistently improve quality while aggressively reducing cost. Lean and six sigma

methodologies empower organizations to achieve these goals even in adverse economic

situations. The sooner we realize this, the better.

We strongly believe that Six Sigma is not just a methodology, but a way of life. The

organizations are yet to mature in this concept.

We, as an institute, wish to act as a catalyst in bringing about this awareness by

felicitating those who have reaped the benefits of using six sigma methodologies.

We, at SCMHRD, constantly strive for perfection in every endeavor that we undertake.

We thank the corporate for enabling us in grooming our students in this regard and also

for making this event a well branded one in an international context.

Best Wishes,

Dr. Pratima Sheorey

Director,

SCMHRD

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Wipro Technologies

Applying Lean for Streamlining Client Conversion Activity

The customer is a Global Custodian Bank (GCB), one of the oldest institutions in North America

and one of the world’s largest asset management companies with trillions of USD under

management. It is responsible for custody and administration of 11% of the world’s total financial

assets and 40% of the US mutual funds market. It also provides 80% of the world’s largest money

managers and asset owners with foreign exchange and transition management services, and

quantitative research and technology-driven tools.

Wipro is engaged with the GCB in a large multi-year engagement for 24x7 for L4 support.

About Project

Project is designed to support and maintain one of the Data Warehouse Application for the client. It

provides a complete middle and back office solution to clients. It gives asset owners and managers a

dynamic, customizable, and scalable self-service platform for all their data needs. Powered by

superior accounting and performance capabilities and fully integrated with award-winning

information delivery capabilities, it provides an end-to-end solution. This application is an Oracle

Database, as a DataMart for the temporary storage sets for Data received from one of the upstream

application. Application is responsible for the delivery of extracts to majority of clients and third

parties. All these data extracts are extremely time critical. It is a high availability application which

needs to achieve predefined client expectations and SLAs. Even the slightest of outages on the

application can have huge financial and reputational losses to the company the application caters to

end users all over the world hence needs to be up and running 24x7, 365 days with minimal planned

downtime or outages. On an average there are 3 Client conversions every month

Problem

Client conversion activity is critical client onboarding process which involves end-to-end

environment configuration and testing of data flow and delivery of data extracts. Conversion

activity is highly effort intensive and time critical process with multiple manual activities would

take more than 70 Hours/Conversion. The success rate of the conversion was 46% leading to huge

rework effort and delay in end client onboarding. Delay in client onboarding had huge financially

loss to end client and financial penalties for customer.

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Approach Taken

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Lean Tenets Applied

Fishbone analysis was applied to identify the problems

which are associated with the conversion activity.

• Unstructured process

• Issues while processing Data

• High MTTR

• Infra Issues The manual tasks were identified and many of them were

Automated to make the process mistake proof and save

manual efforts.

• Manual deleting of aged log files.

• Manual refresh of data

• Manually triggering of data processing.

5 WHY Analysis was applied to identify the root cause of

application issues.

• Issues with data rearrangement

• Issues with data refresh

• Unstable Application instance

Information Spaghetti was applied to stream line the

communication channels during Conversion activity

• The waste in the communication process involving

multiple parties.

• The number of communication channel came down

from 12 to 2 Standardization was applied to streamline the Conversion

activity.

• List of activities along with the time lines [pre and

post conversion]

• Details of known issues & Link of the SOPs

• Contact list of the Team involved during

conversion activity etc.

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Results and Business Impact

Streamlined Conversion activity.

Efficiency

Overall effort for client conversion reduced to 25%

Key highlights

• Increase in Customer Satisfaction

• 100% Success Rate

• 25% reduction in overall Effort

• Reduction in 47% of rework

75%

100%

33.33% 33.33%

0%

100% 100% 100% 100%

0%

20%

40%

60%

80%

100%

120%

00.5

11.5

22.5

33.5

44.5

Month1 Month2 Month3 Month4 Month5 Month6 Month7 Month8 Month9

Before Before Before Before Before After After After After

Success Rate

No of Conversions Successful Conversion Conversion Success Rate%

4

2

3 3 3

1

2

3

1

3

2

1 1

0

1

2

3

1

84

96

64 64

48 48 48 48 48

0

20

40

60

80

100

120

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Month1 Month2 Month3 Month4 Month5 Month6 Month7 Month8 Month9

Before Before Before Before Before After After After After

Effort Spent

No of Conversions Successful Conversion Effort Per conversion

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Wipro Technologies

Storage Space Optimization and SAN Recovery

The Client

SNXT is a remote support center where infra-management is done remotely for multiple customers

on shared basis. One of the domain/technology supported is Storage domain. 45+Customers

supported by domain are from all the different vertical i.e. BFSI, Government, ENU & Retail.

Deliverable

As part of domain support from SNXT remote infrastructure management team, Storage team has to

ensure the storage space consumption below the threshold of 80% to avoid application slowness,

business downtime etc as per the defined service levels. Team has to maintain sufficient free space

for the high availability of server/service for the customers DC Infra.

VOC:

In the Q1 of FY 2018-19, Storage team received multiple Customer concerns related Server

slowness, Drive disconnection and Performance issues. Team analyzed the storage health report of

May’18 to Jul’18 and observed that, storage space consumption was crossing the threshold limit of

80% (was varying from 85% to 95%).

High storage space consumption leads,

• Application slowness

• Business downtime

• Revenue loss to customer

• Reputation damage

• Low CSAT

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Business Situation

DC IT Infra is backbone for the entire IT services it is important and critical that always sufficient

storage free space should be maintained & consumed space should be under the threshold limit.

Being a shared infrastructure for multiple servers belonging to multiple Customers space constraint

will lead to range of business issues to Customer including business outage.

We have intended to work on Storage Space Optimization in shared domain accounts, to decrease

issues related to “space constraints”. This will further contribute in decreased risk of unplanned

downtime in DC operations which in turn will be resulted in avoidance of potential productivity

leakage from engineers, increase operating margin for Centre & enhanced the customer satisfaction.

How we Helped…

Automation: With the help of automation Script, team has automated the SAN backup activity,

which is prerequisite for performing any storage related activity and is resulted in elimination of

manual intervention, reduced the time for taking the SAN backup and also Team has enabled IOPS

reports which help in identifying the live status of live read & write operations of storage volume.

Poka-Yoke (Mistake Proofing): User ID has been created with the security admin property and has

only the authority to execute Config-upload command which will avoid wrong command execution

from Engineers while taking SAN backup.

Capacity Planning: Individual application wise storage space allocation/reclamation trends are

analyzed and reports were shared with Customer.

Individual month wise storage space allocation/reclamation of Storage product wise trends are also

shared with Customer as a part of pro-active planning.

Standardization: Mandated not implement any critical changes which are cause for business

services unavailability. Created a standard operating procedure for storage space reclamation. To

enhance the Engineer’s knowledge internal training sessions were conducted

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Challenges faced

• Convincing the Customer access privilege and space for saving SAN backups

• Inter domain coordination

• Coordination with Vendor/Customer

Benefits

• Business Benefit: Reduced the time taken for

SAN switch configuration backup activity

from 18 hrs/week to <1hr/week. Which

resulted in operational cost saving of INR

1.2MN/Year.

• Customer Benefit: Due to our extensive

efforts in reclaiming the space, we were able

to benefit Customer by reclaim 80TB space,

which is equivalent to the cost saving of

approx. INR 6MN.

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Wipro Technologies

Productivity Improvement for a Major Step

Problem Statement:

During the period 11th Nov’17 through 29th Dec’17 average Ckmph for subject step was around

4.08 as against target of 4.3 for Q4’17.

Wipro team studied the process in detail through Value Stream Mapping (VSM). This study helped

us in identifying Non-Value adds in the existing process.

In the existing process, Operator had to revisit same set of evidences to model a particular parameter

thereby spending additional time in modelling the complete AOI. Wipro recommended a change in

methodology (Pan and Scan) which reduced the time spent in referring to the same evidence

multiple times.

Approach:

• Pilot team comprising of 7 people worked on this step using new methodology that fetched

good productivity benefits without compromising on quality.

• Based on the benefits realized from the pilot batch, all the teams were asked to follow new

methodology.

• This proactive idea of Wipro was highly appreciated by the client and they gave approval to

proceed with the strategy in order to improve the overall product. Wipro took ownership on

the end-to-end process and demonstrated capability to deliver It on time. Wipro modified the

process workflow and provided the quick action plan for output improvement.

• Client also implemented the new change in their latest version of the tool. This action plan

helped in sorting out the issues and successfully completing the project with benchmark

performance

Business Benefits

• Productivity improved by 59%, from 4.08 Kmph to 6.5 Kmph

• 4K+ hours/month of productivity benefits realized with a $ impact of $20645

• Wipro’s new approach was deployed in the customer tool at an Enterprise level.

• Wipro’s new work approach helped the business to enable the deployment in the step, it

helped the customer to reduce the rework time by 50%.

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Wipro Technologies

Reduction in Cycle Time for Sales Live Chat Process

Necessity of doing this Project and Current Status

This project was done for one of the largest telecommunications company, offering a full range of

communication services and competing in all telecommunications markets. Sales Chat is one of the

processes outsourced by this Australian telecom giant to Wipro. Wipro is responsible for handling

chats and for converting them into sales (pertaining to core and ancillary).

It was observed that the average chat cycle time in the period between 1st Dec 2016 and 15th Jan

2017 was 1567 seconds and a reduction in NVA by 15.76% approx. has a potential to create

capacity in the process thereby increasing the number of sales and in turn increase Telstra’s revenue

by over AUD 15 Million. The project will also impact customer experience and NPS for the

process.

One-Sample T: Chat Cycle Time in seconds

Test of μ = 1320 vs ≠ 1320

Variable N Mean StDev SE Mean 95% CI T P

Cycle Time (seconds) 40 1566.6 124.8 19.7 (1526.6, 1606.5) 12.49 0.000

Improvement Opportunity

A Value Stream Map was drawn to understand the steps at a click level and determine the flow of

the process in order to identify the various wastes associated with it. Key inferences drawn are as

given below

✓ Wait time contributed to 12% of the total time since the advisors had to wait in chat to get

sales reference ID from the customers as well as for customer response to chat and system

latency

✓ Over processing contributed maximum to the total waste as probing and need analysis were

not standardized and a lengthy process was followed for account authentication

✓ Value Add contributed to only 24% of the total time

✓ A lot of time was taken in referring to multiple documents, websites, SOPs and chat window

✓ Advisors had to complete multiple documentation post completion of one chat and before

initiating another

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Solutions and Implementation Plan

✓ Product specific canned responses, soft responses for objection handling was prepared by

the training team and approval taken from the customer to implement the same

✓ Mistake proofing of standard responses

✓ Need analysis tailored for both new and existing customers to ensure continuous flow in the

process

✓ 5s technique implemented to ensure advisors were able to search for the required

information faster and lesser documents were referred to

✓ Kanban used to signal to supervisors in case the chats went beyond 30 minutes of AHT

✓ Process change was implemented to ensure that the advisors don’t need to wait in the chat

to get the reference ID

✓ SMED used to reduce the change over time between two chats

Risk analysis was done before implementing the solutions and a sign off was taken on the To-Be

SOP. Control Plan and Control Charts were rolled out to ensure the metric was monitored and

controlled by the project team.

Metric Improvement and Benefit

Post improvement of the metric, hand off document was signed off to transfer ownership to the

process owner. Approvals was taken from the concerned stakeholders to close the project

Benefits Realized:

Annualized increase in revenue for Wipro worth AUD 261,744 or INR 1,27,01,942

Annualized increase in revenue for client worth AUD 16,793,857 or USD 12,618,904

Reduction in Cycle Time from 1567 seconds to 1223 seconds

NPS improvement equivalent to + 12 points

Two-Sample T-Test and CI: Cycle Time- Pre, Cycle Time- Post

SE

N Mean StDev Mean

Cycle Time- Pre 40 1567 125 20 Cycle Time- Post 38 1223.4 78.1 13

Difference = μ (Cycle Time- Pre) - μ (Cycle Time- Post)

Estimate for difference: 343.2 95% CI for difference: (295.9, 390.4)

T-Test of difference = 0 (vs ≠): T-Value = 14.47 P-Value = 0.000 DF = 76

Both use Pooled StDev = 104.7269

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Wipro Technologies

CPE Cycle Time Reduction

About Client: Client is one of the UK’s leading telecom service provider operating in more than

170 countries in the world. Wipro’s engagement with this client includes O2C (Order to Cash) and

operations handled from Pune & Chennai locations. Global service is one of the process where

Wipro is responsible for End to End delivery; starting from Sales order to the Installations of the

services at client’s locations.

Business Challenge: The process was facing the challenge of higher delivery timeline of

CPE/routers; ~70 days against the target of 50 days. This has resulted revenue loss, unnecessary

supplier cost for access & led to customer dissatisfaction during the period of May’16 to Aug’16.

The reasons were unknown and process had to deal with multiple escalations during that period.

Approach:

Baselining of As Is

Identification of Xs -Brainstorming

Priortization of Xs -Multivoting

Analyze of all priortized Xs -Regression & other analysis

Improvement of all Xs

Sustenance of improvements

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Solution:

Benefits:

✓ Early revenue realization of $ 8.84 Million per annum

✓ Reduction in CPE delivery timeline by more than 20 Days

✓ Reduction in Customer Escalations

✓ Increase in efficiency

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Wipro Technologies

Program Weight Loss by Incident Reduction

The Client

Service NXT is Wipro’s next-generation Integrated Services Platform for Remote Infrastructure

Management, designed to Improve Service Resiliency, reduce operational costs and drive closer

Business alignment.

Currently Service NXT supports 100+ customers, 13+ technical domains, 20+ services across 24*7

for India business Wipro.

Deliverable

An Incident is unplanned disruption /degradation of service. Service NXT being a remote

infrastructure management team, have to ensure the high availability of Customer infrastructure by

managing the Incident on time with minimal impact to Customer.

VOB / VOC:

Issue of increasing Customer business impact hours, due to increased incident count was one of the

major point of discussion during Governance / review meetings.

Rise in incident count was further contributing in increased unplanned downtime, in DC operations,

which in turn leading to potential productivity leakage from engineers. Also decreased operating

margin for Centre & increase in customer dis-satisfaction.

Business Situation

▪ We have evidenced a surge in Incident following business dynamic of multiple client

supported for remote DC infrastructure management. Which was leading to degradation of

service and intern influencing to Operation cost for organization and hampering customer’s

perception.

▪ Considering DC IT Infra is backbone for the entire IT services it is important and critical that

these incidents must bring under control, to improve the Cost of operation and CSAT. Overall

reduction in number of Incidents will lead to a decreased unplanned service downtime of DC

operations and better response, resolution from engineers, as they can concentrate more on

genuine Incidents.

▪ As a part of Incident reduction drive, we have envisaged to reduce the Incidents by 40%.

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How we Helped…

Automation: To increase the efficiency for Auto Heal solutions (Holmes Orchestrator Efficiency%)

implemented logics such as Repetitive Alert Algorithm [RAA], Sequential Pattern Matching [SPM]

& Magnitude Correction [MC], Weighted Time Over Threshold [WTOT]

& Cross-Domain Dampening & Correlation [CDDC].

Automation done for transactions in Holmes Orchestrator, where in Incident will be firstly worked

on by machine and incase issue persists same will be send to engineers.

Capacity Planning: Constraints in resources of DC infra as per business need are addressed

through Capacity planning. Wherein Overall 863 Proactive Problem Ticket logged for Noise

Making Asset, based on Incident analysis. As per the RCA of Problem tickets, actions were taken on

capacity enhancement.

Poka-Yoke (Mistake Proofing): Mistake proofing the process of event detection and filtration

levels was done by,

A.RMAN backup space errors fixing through - doing script level changes & Space addition Enabled

archive log mode and configured RMAN backup.

B. Change in threshold for long running queries in STATION01 instance for all the databases.

Mail Notification has been enabled from tools level for Background long running job

c. Upgrading the necessary patches for ORA errors.

availability monitoring scope definition - if 24x7 support, monitoring enabled for 24x7, for rest as

per user service window monitoring window is changed with customer Approval.

Standardization: Standardization for transaction and procedure were done as follows:

A. Housekeeping activities are scheduled through scripts

B. Upgrading the necessary patches for ORA errors were done

C. Standardization of log shipping activities were done

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D. Reviewed and revamped technical domain wise monitoring parameters

E. Fine-tuned Background jobs running for the longer time was done.

Challenges faced

• Scale/vastness of the activity

• Inter domain coordination

• Reducing the incidents without impacting the Customer infrastructure.

Benefits

• 67% Reduction in Incident volume (i.e.

from 1658 incident to 549 incidents per

day)

• Customer business impact hours reduced

by 70% (i.e. from 210,000 Hrs. to 63,000

Hrs)

• Incident per CI reduced from 2.43 to 0.71

• 90% Reduction in manual error

• Process adherence score improved to 99%

(Aug’18) from 96% (May’17)

• 31% increase in NET Promotor Score

• INR 2.9 Cr Cost saved

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Wipro Technologies

NPS -Enhancing Provider Experience in Healthcare

1. Problem Statement

•The overall Provider Experience is impacted by various active & passive Provider Touchpoints in

the Claim Processing journey. Basis the overall provider NPS survey feedback, Top 10 Provider

Pain points are contributed by 3 Key Business Areas (PDO, Claim Processing and Provider

Services) in the E2E Claims Lifecycle.

•Basis the performance levels (May’17 to Sep’17), Wipro NPS is trending at +46.5 as against Client

Global Score of +52 impacting the overall provider experience

2. Situation Analysis Overview

Situation Analysis: Following the DMAIC approach, the relationship analysis was done between the

Provider Pain Points and the Business areas impacting them. The Key Metrics impacting the

Provider Experience are Accuracy of payment and Timeliness for specific Identified Business

Areas. A detailed analysis was done to identify the root causes at a metric level using Statistical

Analytics and Predictive Tools.

Solution: Transformative solutions leveraging proprietary Cognitive, Machine Learning and Natural

Language Processing technologies were deployed to re-design the process with shift of

accountability to bots reinforced with AI capabilities.

Benefits: Improved Provider Experience, Cost Reduction, Reduced Rework & Enhanced Efficiency

- Fit for Future Processes

3. Buy-In and Results Overview

Wipro participated in weekly review meetings with the Onshore Teams and project sponsors/

champions

Buy In and Positive Feedback received from all Key Stakeholders from each of the Business Areas

Results Achieved:

• Sigma Multiple (Provider Experience) improved from 0.80 Sigma to 1.55 Sigma with NPS to

+52

• Enhanced Quality of service, Efficiency and TAT for PDO, First Pass and Provider Services

• Annualized Overall Benefit of $8.5 MN

• Scalability and Institutionalization Benefit of $10MN+

• Overall Provider NPS Improvement

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Aditya Birla Fashion and Retail Limited

Efficiency improvement in Jacket Line 3

Project

Background

Jacket line3 Efficiency is 63% with an average output of 750pcs for the period

of Sep’17 to Nov’17 against the targeted efficiency of 80% with an output of

1000pcs which is resulting in estimated opportunity loss of 250pcs and the

expected revenue loss is Rs.42,50,000/-

Project

Goal

To Improve the Jacket line3 efficiency from 63% to 80%

Approach

The Six sigma DMIAC methodology has been used in this project

Define

Phase

In the Define phase, the business case, the Jacket manufacturing process flow,

project CTQ are defined with tools such as project charter, SIPOC, CTQ

specification table respectively.

CTQ SPECIFICATION TABLE:

CTQ

Operational

Definition of

Measure

Specification

Defect

Definition

KANO

Status

Measure

Phase

In the measure phase data collection plan was carried out for the project CTQ.

The current status of the CTQ was measured using process Capability analysis.

The observed PPM, mean and standard deviation was established.

#

S.NO.

CTQ N Normality

Test

Mean Standard

Deviation

PPM Sigma

Rating

1 Efficiency 76 Normal 0.627 0.0557 1000000 0

Analyze

Phase

In analyze phase, statistical analysis such as Descriptive analysis and regression

analysis was carried out to identify the relationship between sub section efficiency and

the line efficiency. It was observed through the statistical analysis that 89.2% of

variation in the line efficiency is due to the efficiency of body section and the

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efficiency of body assembly section. This was validated again through scatter plot and

a positive correlation between body efficiency, body assembly efficiency and line

efficiency was observed. All the possible cause for low efficiency was identified

through cause and effect diagram and the causes was prioritized using FMEA. The

major root causes emerged out of analyze phase is as follows:

SI No. Root Cause Tool Used

to Validate Result of Validation

1 Low

performers

Capacity

graph

1. Lining sleeve seam

2. Sleeve inseam

3. Front edge 15 Cm tape attach

4. Neck close

5. Front edge cut

6. Cotton bias tape attach

7. Collar open seam ironing

8. Sleeve attach

9. Dart ironing

10. Main label zig zag

2 High

rework

1.Regression

analysis

2.Pareto

chart

1.Negative correlation is observed between line

DHU and line efficiency.

2. The top defects in body and body assembly are

pick shape improper, Front edge lifting and dart

dimp

3 work

content

imbalance

TAKT time

analysis

Through TAKT time analysis some of the low

work content operations were identified. Those

are,

1. Neck marking and bottom marking

2. Front edge seam and front edge tacking

4 High

absenteeism%

1.Scatter

plot

1.Negative correlation is observed in between

absenteeism and line efficiency.

Improve

Phase

The team brainstormed and came up with solutions to eliminate the root causes. The

details are as below

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Root Cause Solution Matrix

Through brainstorming, solutions were identified for the root causes.

Risk analysis was carried out to identify and evaluate the side effects and it was

identified that there were no major side effects. Implementation plan was laid out

involving the cross functional teams such as Production, HR, Quality and IE

Result

The results were evaluated using box plot and Process capability analysis, 2 sample T

test.

Root cause Solution Tool Used

Low performers

(11 bottleneck

operations

identified)

1.Training operators in identified bench

mark method operations for clearing the

bottleneck operations.

2. Redesign the layout

Video

Analysis

Software

(VAS)

Top 3 defects were

identified in body

and body assembly

sections (Pick

shape improper,

Front edge lifting)

1. Work place re-engineering

2. Introducing folders and

attachments to enhance the

product quality.

Kaizen

Low Work content

in operations

against SMV Vs

TAKT time

Combinations of operations to have a

balance work content across the line. TAKT time

graph

High

absenteeism%

1.Implementation of pre-planned leave

system

2. Implementation of attendance bonus

system

3. Employees engagement programs A3

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Control

Phase

The improved process was standardized through operational SOP, Line layout, Planned

leave system, multi skill report to ensure sustenance of the results.

# CTQ

N Average S.D PPM Sigma

Level

Before Efficiency 76 0.6278 0.0557

1000000 0

After Efficiency 76 0.8113 0.0153 184210 2.39

AAROHAN 2018


26

Ashok Leyland Limited

To reduce the rejection of the Synchro parts from current level of 1070 PPM

to 535 PPM (50% reduction) at Heat Treatment line by Dec’17

Executive Summary: Ashok Leyland has seven manufacturing locations based at Chennai, Hosur

(2 plants), Ennore, Bhandara, Alwar and Pantnagar. We are representing Bhandara Unit, a

transmission plant manufacturing Synchro-mesh Gear Boxes with technological collaboration with

ZF - Germany. The Plant is having state-of-the-art machinery and equipment to produce world class

transmissions. Organization is becoming lean not only to sustain competitive edge but also to

become a global player. Our Bhandara unit has many accolades to its credit; some of them includes

India Manufacturing Excellence Award, Rajiv Gandhi National Quality Award, Ramakrishna Bajaj

National Quality Award, LESSA’2013 Runner up award, Golden Peacock National Quality Award,

CII EXIM bank award etc.

Problem Selection & Linkage to Strategy: Ashok Leyland has driven various initiatives to

improve the customer satisfaction by solving the various customer concerns (internal and external)

by using lean six sigma approach. This has prompted to revisit and reduce the rejection of synchro

components. The high rejections of the synchro parts at heat treatment impacting the delivery

schedules of entire Bhandara plant and additional manpower was required which further increases

operating cost. Hence the project has been taken by heat treatment team to solve the above-

mentioned concern. This will result in financial saving of INR 2.06 lakhs per annum.

Scoping of the Problem: From Fig a, P chart concludes that rejection PPM of synchro parts was

1071 PPM for last 9 months. The pareto chart in Fig. b shows contribution of the rejection of

synchro parts at heat treatment. Fig. c shows reason of rejection of synchro parts at heat treatment.

Fig a Fig b Fig c

Define: The charter was approved by the management, a SIPOC diagram was done to understand

the relationship right from Supplier, Process to Customer. Relevant CFT team was accordingly

formed and driven by GB, with the support of BB and Sponsor. Framework for reviews with all

stakeholders finalized. The team worked on the process map and identified the KPIV and KPOV’s

in shown in Fig d.

Dec.

16FN1

Nov.

16FN1

Oct

.16FN1

Sep.1

6FN1

Aug.1

6FN1

Jul.16FN1

Jun.1

6FN1

May1

6FN1

Apr.

16FN1

0.00175

0.00150

0.00125

0.00100

0.00075

0.00050

Month

Pro

po

rtio

n

_P=0.001071

UCL=0.001560

LCL=0.000581

Tests performed with unequal sample sizes

P Chart of % defectives

Qty. 11243 152 61 60 57 36 28 24

Percent 1.636.2 22.6 9.1 8.9 8.5 5.4 4.2 3.6

Cum % 100.036.2 58.8 67.9 76.8 85.3 90.6 94.8 98.4

Reason

Other

Teeth da

mag

eBe

nd

Scoo

p da

mag

e

Welding

not ok

Gap be

twee

n was

her &

cone

more

High

ECD

Scaling

Low surface

har

dnes

s

700

600

500

400

300

200

100

0

100

80

60

40

20

0

Qty

.

Pe

rce

nt

Pareto Chart of Reason of Rejection of synchro components

AAROHAN 2018


27

Fig d Fig e

Measure: Listed 12 probable causes through fish bone diagram after brainstorming as in Fig e,

which was further refined through cause & effect matrix. Variable MSA was done for 10 parts with

3 appraisers and 2 replicates for surface hardness inspection on Digital Rockwell hardness tester as

in Fig F. Total Gauge R & R is 8.1 %, which is < 10%, hence the measurement system is capable.

Analyze: The team used Lean Six Sigma methodology for funneling of X’s and with improved &

streamlined data collection process, studied the effect of different input variables on output variable

using regressions, box plots, standard deviation test, one-way annova & multi-vari analysis, refer

Fig g, Fig h, Fig I, Fig j & Fig k.

Fig f Fig g Fig h

the parts in the study.

measurement system. The process variation is estimated from

8.1% of all process variation can be attributed to the

100%30%10%0%

NoYes

8.1%

ReproducibilityRepeatabilityTotal Gage

48

36

24

12

0

30

10

% of Process

the total variation in the process.

accounts for 0.0% of the measurement variation. It is 0.0% of

occurs when different people measure the same item. This

-- Operator component (Reproducibility): The variation that

It is 8.1% of the total variation in the process.

times. This accounts for 100.0% of the measurement variation.

occurs when the same person measures the same item multiple

-- Test-Retest component (Repeatability): The variation that

and use this information to guide improvements:

Examine the bar chart showing the component contributions,

>30%: unacceptable

10% - 30%: marginal

<10%: acceptable

General rules used to determine the capability of the system:

Number of parts in study 10

Number of operators in study 3

Number of replicates 2

Study Information

(Replicates: Number of times each operator measured each part)

Gage R&R Study for Measurements

Summary Report

Variation Breakdown

reproducibility?

Is there a problem with repeatability or

Comments

Can you adequately assess process performance?

components

synchro

scaling in

hardness &

Low surface

Environment

Measurements

Methods

Material

Machines

Personnel

O perator

Delay Q uench

C y cle time

Furnaces

C arbon potential

Hardening temp.

materialM ix up in input

Decarb

per trayNo. of components

Soaking Time

Inspection error

Power failure

Fish bone diagram for low surface hardness & scaling in synchro components

significant (p < 0.05).

The relationship between HRA and temp is statistically

> 0.50.10.050

NoYes

P = 0.000

the regression model.

83.98% of the variation in HRA can be accounted for by

100%0%

R-sq (adj) = 83.98%

860840820800780

85.0

82.5

80.0

temp

HR

A

81

causes Y.

A statistically significant relationship does not imply that X

for HRA.

temp that correspond to a desired value or range of values

to predict HRA for a value of temp, or find the settings for

If the model fits the data well, this equation can be used

Y = - 1492 + 3.789 X - 0.002276 X**2

the relationship between Y and X is:

The fitted equation for the quadratic model that describes

Y: HRA

X: temp

Is there a relationship between Y and X?

Fitted Line Plot for Quadratic Model

Y = - 1492 + 3.789 X - 0.002276 X**2

Comments

Regression for Surface hardness (HRA) vs Hardening temperature

Summary Report

% of variation accounted for by model

(p > 0.05).

Differences among the standard deviations are not significant

> 0.50.10.050

NoYes

P = 0.813

Operator 2

Operator 1

Operator 3

1.00.80.60.4

standard deviations at the 0.05 level of significance.

You cannot conclude that there are differences among the

1 Operator 3

2 Operator 1 None Identified

3 Operator 2

# Sample Differs from

Which standard deviations differ?Do the standard deviations differ?

Standard Deviations Comparison Chart

Comments

Standard Deviations Test for Operator 1, Operator 2, Operator 3

Summary Report

AAROHAN 2018


28

Fig I Fig j Fig k

Improve: Three major improvements done to reduce the rejections of synchro parts from the

furnaces.

1. Design of experiment (DOE) is done on three significant input variables which are affecting on

output variable and process parameters freeze as shown in Fig. l.

2. Mistake proofing’s i.e. error proofing’s provided for hardening temperature, carbon potential,

soaking time & scaling in the furnaces as shown in Fig. m.

3. Audio alarm provided for delay quench time in rotary hearth furnaces as shown in Fig. n.

Fig l Fig m Fig n

Control: 1.QMS documents of heat treatment updated based on parameters.

RHF5RHF4RHF3RHF2RHF1

83.5

83.0

82.5

82.0

81.5

81.0

80.5

80.0

FurnacesS

urfa

ce

Ha

rd

ne

ss (

HR

A)

Boxplot of Surface Hardness (HRA)

Carbon Potential*Hardening Temperature

840825810795780

1140

1125

1110

1095

1080

Delay Quench*Hardening Temperature

840825810795780

40

30

20

10

Delay Quench*Carbon Potential

11401125111010951080

40

30

20

10

Hardening Temperature 830

Carbon Potential 1125

Delay Quench 20

Hold Values

>

–

–

–

–

< 78.0

78.0 79.5

79.5 81.0

81.0 82.5

82.5 84.0

84.0

Hardness

Surface

Contour Plots of Surface Hardness

Differences among the means are not significant (p > 0.05).

> 0.50.10.050

NoYes

P = 0.989

5 min

2 min

4 min

3 min

82.582.081.581.080.5

means at the 0.05 level of significance.

You cannot conclude that there are differences among the

1 3 min

2 4 min

3 2 min None Identified

4 5 min

# Sample Differs from

Which means differ?Do the means differ?

Means Comparison Chart

Comments

One-Way ANOVA for 2 min, 3 min, 4 min, 5 min

Summary Report

AAROHAN 2018


29

Cost Benefit: Realized Savings INR Rs.

2.06269/- lakhs vetted by Finance & IED for

2017-18.

Sustenance Monitoring: The team monitored

the sustenance of the project metric as shown in

Fig. o till Jul.18.

Jul.18FN1

Apr.

18FN1

Jan.1

8FN1

Oct

.17FN1

Jul.17FN1

Apr.

17FN1

Jan.1

7FN1

Oct

.16FN1

Jul.16FN1

Apr.

16FN1

0.0018

0.0016

0.0014

0.0012

0.0010

0.0008

0.0006

0.0004

0.0002

0.0000

Month

Pro

po

rtio

n

_P=0.000471

UCL=0.000806

LCL=0.000135

Before project During project After project

Tests performed with unequal sample sizes

P Chart of % defectives before vs after

Also, project is monitored through Daily management initiatives taken by Ashok Leyland Ltd. for

sustenance as shown in Fig. p.

Fig.p.

Fig. o

AAROHAN 2018


30

Godrej Consumer Products Limited

Journey Towards a Leaner and efficient Supply Chain

Godrej Consumer Products is a leading emerging markets company. Today, our Group enjoys the

patronage of 1.15 billion consumers globally, across different businesses. In line with our 3 by 3

approach to international expansion at Godrej Consumer Products, we are building a presence in 3

emerging markets (Asia, Africa, Latin America) across 3 categories (home care, personal care, hair

care). We cater to diverse market segments ranging from mass marketed products such as No.1

soaps to highly niche value added products such as Godrej AER car freshener. More than 60% of

our revenue comes from seasonal products.

Supply Chain Journey

GCPL was the first FMCG company in India to adopt REPLENISHMENT as a core theme for

serving its internal and external customers. The Theory of Constraints, as proposed by Dr. Eliyahu

Goldratt was used to design the initial supply chain strategy and network

AAROHAN 2018


31

Need of Project

As evident, by FY -16, we reaped benefits of Replenishment with our legacy systems and observed

a reduction in stock outs. But similar control over inventory couldn’t be met, which led us to think

the root causes behind this

Root Causes

Complexities in supply chain were due to (a) Increasing stock points, (b) Business seasonality (c)

Focus on NPDs

INTERNAL SURVEY WAS DONE AND REASONS CLUSTERED IN

UNDER ‘VUCA’ FRAMEWORK. COMMON THEMES WERE

Lack of VISIBILITY e.g. non-accessibility of granular sales data on a

daily basis

Inadequate PREDICTABILITY e.g. Impact of past Sales trend on future

estimates

Both of these led to SUB-OPTIMIZATION of relevant processes.

Gaps Observed Across Supply Chain Practices

AAROHAN 2018


32

An Integrated Solution Was Brought to Address Gaps

UNIQUENESS OF IMPLEMENTATION

GCPL was first Indian FMCG to

• Implement Replenishment in APO & ILOG

• Daily movement of truck from all

connecting nodes

• Daily-planning buckets for optimization

• Rigor of Operations research techniques

e.g.

Linear Multivariate Optimization

Forecasting Methods

• APO as a Service-level Optimizer, not as

Cost optimizer

• Crisp, relevant data for fast decision-

making

AAROHAN 2018


33

Reliance Retail Limited

To Reduce Energy Use and Cost

Energy is second largest operating expenses in Retail business. Retail is working on very stiff profit

margin so the saving in electricity bill for each store will directly lead to increase in profitability of

the business. This will add up directly to the bottom-line. At present RRL total electricity cost is

approximately Rs.600Cr/Yr.

Through this project we aim to reduce energy cost by 8%.

Total expected cost reduction by Rs. 22.63 Cr.

AAROHAN 2018


34

Tata Autocomp

Simplification of Supply Chain of Ashok Leyland Engine Hood (G91&G45)

Through Development of PU Foaming Technology

Problem Statement:

This project aims to simplify the existing supply chain of Ashok Leyland as per their special

requirement. A non-melting and fire-retardant PU foam formulation having zero mm/min burn rate

with improved acoustic performances and required mechanical properties has been developed in-

house as an insulation package as per their requirement. As a result, we are able to directly supply

the assembled hood to the OEM instead of supplying the only hood to their vendor. This helped us

for substantial enhancement in Top and Bottom line and delighted the customer by simplifying their

Supply Chain.

Results Obtained:

➢ Forward integration leading to doubling of part Sale value.

➢ Opportunity for horizontal deployment to TML, Daimler etc.

➢ Revenue enhancement approx. 25 Cr.

➢ Potential business including product family approx. Rs 15 Cr

➢ Simplified supply chain for customer – Logistics cost reduction, lower lead time.

➢ Immediate effect on bottom line of the organization

➢ Wider scope to offer complete solution to customers

➢ Establishment of approach to work for new technology area

➢ Patent generation for the Organization at Indian Patent Office (IPR)

➢ Become Tier-I supplier of Ashok Leyland

➢ Full system supplier for engine noise & heat insulation management

Customer Benefit:

Simplification of Supply Chain- Lower Lead Time as well as Lower Logistics Cost

AAROHAN 2018


35

Tata Consultancy Services

Improve Time to Serve for Activation Process

Introduction

Our client being one of the major player in APAC region and with a level playing field in

the Australian fixed line business our client had to improve customer experience and still

maintain market share of > 50%.

TCS process manages customers request after a sales order is placed by Front of House

(FOH) until the time customer is connected to the broadband services. Associates make an

outbound call, receive inbound calls and also do back of house work for service fulfilment.

Expected volume for the process is forecasted to increase by 58% which would lead to

increase in Cost to serve for the client. This has led the client to explore price

competitiveness and innovative ideas for reducing time to market, cost and improve

customer experience.

Focus to improve process efficiency through process redesign without any impact on the

quality of deliverables and end customer satisfaction is the key objective of this project.

Problem Definition

At the current efficiency the forecasted increase in the volume would result into increased

headcount and cycle time for the process. Order processing timer per order for the process is

trending at 3.82 hours in Jan18 with monthly volume of xxx sales per month

Generate/ Harvest Ideas & Solutions:

• Order Build Intelligence (Robotics TOSCA): Tool to be created for fetching

Phone Number/ Username and update order info as per business rules. Tool to

provide detailed report if there are any fall-out

• Automated task allocation: An order intelligence platform to be developed for

report generation and assign the order automatically

• Intelligence Platform: 2 Way SMS to be enabled for providing the automated

order status to customer

• Contact Intelligence Engine: Rapid assessment of order health and auto notes

updation through efficient screen scraping. Online order status tracking and

appointment re-schedule to enabled through intelligence platform Instead of

unnecessary calls, sent email and or SMS to keep the customer informed of the

order progress

AAROHAN 2018


36

Tangible Results.

• 8+ Point Improvement in NPS with a BVA saving of 147 mn

• 43% Reduction in cost to serve from $74 to $41

• 35% improvement in cycle time with a saving of 10.7 mn

Jan-18Nov-17Sep-17Jul-17May-17Mar-17Jan-17Nov-16Sep-16

5.0

4.5

4.0

3.5

3.0

2.5

2.0

Month

Ord

er

Pro

cess

ing

Tim

e (

in H

rs.)

_X=2.421

UCL=2.878

LCL=1.964

Pre Impl. Post

1111

Improvement in Order Processing Time

AAROHAN 2018


37

Bharat Forge Limited

Reduction in scrap for Die of Crown wheel from 3.2% to 1.5 % in

forging shop by Jun-2018

Company Description:

Bharat Forge Limited (BFL), the Pune based Indian multinational is a technology driven

global leader in metal forming, having a transcontinental presence across ten manufacturing

locations, serving several sectors including automotive, power, oil and gas, construction &

mining, locomotive, marine and aerospace. Part of Kalyani Group - a USD 3 billion

conglomerate with 10,000 global work force; BFL today has the largest repository of

metallurgical knowledge in the region and offers full service supply capability to its

geographically dispersed marquee customers from concept to product design, engineering,

manufacturing, testing and validation. The world's largest forging company with

manufacturing facilities spread across India, Germany, Sweden, France and North America,

Bharat Forge manufactures a wide range of high performance, critical & safety components

for the automotive & non-automotive sector.

It is India's largest manufacturer and exporter of automotive components and leading

chassis component manufacturer in the world. BFL's customer base includes virtually every

global automotive backed by several decades of experience in component manufacturing &

metallurgy, the company has embarked on an ambitious and exciting journey to redefine its

already existing presence across several critical business verticals such as oil & gas, power,

locomotive & marine, defence & aerospace, metals & mining, construction and general

engineering

Project Category: Six Sigma -DMAIC - Manufacturing

Six Sigma Approach

Six Sigma (6σ) is a set of techniques and tools for process improvement. Six Sigma is a

statistical methodology used to reduce variation and eliminate defects in business

transaction and processes. BFL Lean Six Sigma is an approach to IMPROVE the

PERFORMANCE of organization from the customer’s perspective in business transactions

and processes

Define Phase: Defined Project Charter along with Six Sigma Belt and core team members

• The project was identified in response to the internal VOC (Voice of Costumer)

based on departmental scorecard KPIs which were in RED zone.

• A Cross functional team was formed and the Project Charter defined with key matrix

along with benefits, scope, constraints, CTQ and timelines.

• Project kicked off meeting done by Six Sigma Belt along with CFT with approval

from Sponsor & after saving calculations financial validation

AAROHAN 2018


38

Measure Phase: Team collected the base line data for project Y. Base line mean and

standard deviation is calculated.

• The Pareto Analysis for Defects done and accordingly prioritization done for top 3

defects

• The key defects monthly data for rate of rejection validated along with MSA – Gage

R & R so ensured measurement system variation having no major contribution

• Key source of defects (KPIVs – Xs) found ID under fill, Fin lap / Cold shut and

eccentric punching.

Analyse Phase: RCA / Brain storming sessions were conducted to identify the potential

X’s.

• Series of Brain storming sessions were conducted to identify the potential X’s and

done SIPOC and Process Map Inputs: Critical Inputs 14 Nos, SOP Inputs 25 Nos,

Noise Inputs 4 Nos.

• Further screening of X’s is done by Cause and effect Matrix filtered ratings above

150 Nos – 14 Nos., Ratings from 100 to 150 Nos -10 Nos. and FMEA further drilled

down 3 Xs for high RPN actions.

• The relationship of this vital X’s with Scrap %due to Coldshut and Underfill is

validated in each stage.

• For RCA, Ishikawa Diagram for key defects, Regression Analysis, Contour plot

analysis done

Improve Phase: Key improvement actions identified such as Upset centering “V”Fixture

Modification, Temp. Sensor poka–yoke or recorder to be provided at Ring Rolling.

• Optimised cycle time for ring forming clamping time.

• Implementations of daily work management and performance matrix and operational

Quality Control Plan.

• Process capability analysis shows Cpk for Pin roundness is improved from 0.66 Cpk

to 1.27 Cpk.

Control Phase: Significant change in Production rate is observed and same confirmed

using 2 Sample t test.

• To sustain the improvement, a transparent control plan is prepared for all vital X’s.

• Revised FMEA Updated in QMS quality documents, Various Control types (SOP &

SOC) were implemented and standardized on shop areas.

AAROHAN 2018


39


Capacity Improvement on Line-7 by Eliminating Lean Wastes

Need of Project:

Demand of Crankshafts increased by 42%. Team has been given challenge to increase

capacity without adding any major capital investment & within little time frame. Using

Lean Methodology was the only way to increase capacity. Team used various lean tools to

eliminate the wastes available within process.

Lean Methodology Used:

Select, Clarify, Organize, Run, Evaluate

Select:

Project was selected based on important need of the organization i.e. Capacity

Improvement. Cross functional team is formed to take care of all aspects in project.

Following Metrics were defined based current baseline:

• Increase capacity by 46%

• Reduce Lead time by 65%

• Reduce Scrap by 62%

Clarify:

Process Flow Diagram Mapped is to get clarity of processes to al team members. Team also

has done Value Stream Mapping (VSM) to identify the Cycle Time, VA, NVA, Material

Flow, Information Flow, Quality Issues & opportunities for improvements for all processes.

https://www.bmgindia.com/images/sdasd.jpg

AAROHAN 2018


40

Organize:

Team has done following activities in this phase

• Line Balance chart to understand the required TAKT & Bottlenecks

• Spaghetti mapped to understand travel of part across plant.

• Operator Combination Chart used to analyse the details of Processes

• ECRS (Eliminate, Combine, Reorganize & Simplify) Analysis done

• Based on above analysis 12 Improvement Actions were identified

Run:

Key Improvement activities based on above analysis were implemented to eliminate various

Lean Wastes. All cross functional team were involved in improvements & changes were

validated through 4M Change Management.

Evaluate:

Results of all actions evaluated. Following results were achieved.

• Capacity Improved by 49%

• Lead Time Improved by 65%

• Quality Scrap improved by 68%

• Inventory level reduced by 44%

• Capital Cost avoided

• Operational Cost Reduced

• Inventory Carrying Cost Reduced

All improvement activities were validated through 4M Change Management, PFMEA,

Control Plan & SOP updated.

AAROHAN 2018


41

Tata Consultancy Services

Reject Reduction in Rejects in Order Processing

Introduction

Customer, is one of the Largest Local Search, Media and Advertising Company offering a

personal service tailored for small & medium business in UK.

Problem Definition

At TCS the fulfillment team processes Order received from client’s Sales team which is a

significant activity in the overall process to validate the orders received from Sales which

comprises annual volume of ~118800 orders.

In the month of March 2017, 25% of the Orders received from XXX Sales team were

rejected back by TCS order processing team due to inadequate information to process the

order.

2% of rejects were cancelled due to Sales team not providing the details.

Generate/ Harvest Ideas & Solutions:

• Introduction of Mistake Proof in tool used by Sales to provide information for

product fulfilment, information will not get submitted without mandatory

information

• Weekly Sales performance report on accuracy and completeness % details

provided to Sales team.

• Introduced a workaround when a reject reaches 20 days then the team will take

content from alternative sources to avoid reject loss.

• Provided refresher training to the Sales team to book the reservation slots

accurately for products, sharing feedback on regular basis.

Tangible Results.

• Total Revenue gain (2% of rejects minimized) = $ 1.4 Mn. (Hard saving)

• Additional revenue based on volume increase by better customer experience and

additional time for Sales team to pitch for new business = $ 101.1Mn. (Soft

Saving)

• Total Savings - $ 102.5 Mn.

• This project helped in reducing huge backlog which resulted in Order processing

team not working extended work hours.

AAROHAN 2018


42

Rejects reduced to 18% with Business Value Add of $102.5Mn

AAROHAN 2018


43


To reduce TIR fallout & TIR scrap on Forging Line

Company Description

Bharat Forge Limited (BFL), the Pune based Indian multinational is a technology driven

global leader in metal forming, having a transcontinental presence across ten manufacturing

locations, serving several sectors including automotive, power, oil and gas, construction &

mining, locomotive, marine and aerospace. Part of Kalyani Group - a USD 3 billion

conglomerate with 10,000 global work force; BFL today has the largest repository of

metallurgical knowledge in the region and offers full service supply capability to its

geographically dispersed marquee customers from concept to product design, engineering,

manufacturing, testing and validation. The world's largest forging company with

manufacturing facilities spread across India, Germany, Sweden, France and North America,

Bharat Forge manufactures a wide range of high performance, critical & safety components

for the automotive & non-automotive sector.

It is India's largest manufacturer and exporter of automotive components and leading

chassis component manufacturer in the world. BFL's customer base includes virtually every

global automotive backed by several decades of experience in component manufacturing &

metallurgy, the company has embarked on an ambitious and exciting journey to redefine its

already existing presence across several critical business verticals such as oil & gas, power,

locomotive & marine, defence & aerospace, metals & mining, construction and general

engineering

Project Category: Six Sigma -DMAIC

Six Sigma Approach

Six Sigma strategies seek to improve the quality of the output of a process by identifying

and removing the causes of defects and

minimizing variability in manufacturing and business processes. It uses a set of quality

management methods, mainly empirical, statistical methods, and creates a special

infrastructure of people within the organization who are experts in these methods.

Why This Project:

Total Indicating Reading (TIR) causing poor VDM index, Generating more scrap in next

processes. The selected part having high TIR issue causing imbalance which results more

machining cycle time as well as quality deviation for TIR Fallout and TIR Scrap.

Define Phase: Define the system, the voice of the customer and their requirements, and the

project goals, specifically.

https://en.wikipedia.org/wiki/Statistical_dispersion

https://en.wikipedia.org/wiki/Manufacturing

https://en.wikipedia.org/wiki/Business_process

https://en.wikipedia.org/wiki/Quality_management

https://en.wikipedia.org/wiki/Quality_management

https://en.wikipedia.org/wiki/Empirical

https://en.wikipedia.org/wiki/Statistics

AAROHAN 2018


44

• The project was identified based on internal Departmental KPI Scorecard where

RED Quality KPIs need to be improved with respect to VOC (Voice of Customer)

• Project organization has defined to drive Six Sigma project with cross functional

team involvement from Quality, Production, Maintenance, Engineering to do

teamwork through DMAIC approach to improve the targeted results (CTQs) within

timelines.

• Project kicked off done after initial financial validation and approval from sponsor.

Measure Phase: Measure key aspects of the current process deviations and collect relevant

data; calculate the 'as-is' Process Capability.

• Team collected the base line data for project Y by studying the Critical Processes

from Process Flow Chart. Base line taken of last 6 months’ data and target set.

• Total Gauge R & R (MSA) for TIR measurement system done

Analyse Phase: Analyze the data to investigate and verify cause-and-effect relationships.

Determine what the relationships are, and attempt to ensure that all factors have been

considered. Seek out root cause of the defect under investigation.

• Series of Brain storming sessions were conducted to identify the potential X’s and

done SIPOC and Process Map with 38 Xs taken forward

• Further screening of X’s is done by Cause and effect Matrix filtered 13 Xs and

FMEA further drilled down 3 Xs for high RPN actions.

• The relationship of this vital X’s with TIR Fallout is validated in each stage.

• One-way ANOVA Analysis for Trimmed jobs and padded jobs (P value <0.5).

• Scatter plot for TIR position Analysis.

Improve Phase: Improve or optimize the current process based upon data analysis using

techniques such as scientifically experiments, Improvement Action Plan & validation and

standard work process. Set up pilot runs to establish process capability.

• Cause Validation plan and Improvement actions for Punch Compensation for

Trimmer punch and Padding Die.

• Compensate Control cooling effect and maintain TIR high point at center.

• 2-t Sample test for TIR mean (Decreased) and Box Plot.

Control Phase: Control the future state process to ensure that any deviations from the

target are corrected before they result in defects. Implement control systems such

as statistical process control, production boards, visual workplaces, and continuously

monitor the process. This process is repeated until the desired quality level is obtained.

• Significant change in Production rate is observed and same confirmed using 2

Sample t test.

• To sustain the improvement, Implementation of 4M change management.

https://en.wikipedia.org/wiki/Design_of_experiments

https://en.wikipedia.org/wiki/Process_capability

https://en.wikipedia.org/wiki/Control_systems

https://en.wikipedia.org/wiki/Statistical_process_control

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• Updated revised RPN action plan with Failure Mode Effect Analysis (FMEA)

Results Achieved :

Scrap Reduction Scrap % Reduced from 0.7% to 0.1%

TIR fallout reduced from 5.5% to 0.4 %

Defective inventory reduced 65.0 to 5.0 Ton.

MCD PPM reduced 1220 to 530.

VDM index ( Processing rating ) increased from 40 % to

90%

Cost Aprx. Cost saving Forging + Machining 6.0 MINR / Year

Logistics Unwanted material movement eliminated

Delivery increased from 93% to 97%

Processing cycle time reduced from 53 Sec to 50 Sec.

Moral Processing & Quality inspector moral increased.

Quality

Delivery

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Address:Symbiosis Infotech Campus, Plot No.15,Rajiv Gandhi Infotecch Park, MIDC, Hinjawadi

PUNE - 411057

WEBSITEwww.scmhrd.edu

www. sixsigma.scmhrd.edu

[email protected]

7+(21(6 7+$ 7 &2817 $$52+$1 - Symbiosis Centre for ... · S ix S igma is not on ly abou t co rrecting e rro rs but also abou t continuo usly inno vating wh at seem s perfect and this

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